Kinetic signatures of microRNA modes of action

An Assessment of the Next Generation of Animal miRNA Target Prediction Algorithms

The advent of genome-wide next-generation sequencing technologies has revolutionized the genomic and transcriptomic fields. New technologies also present an opportunity for greater discovery and understanding of post-transcriptional processes, in particular, translational inhibition of transcripts by miRBP (microRNA-RNA binding protein) complexes. Not only have novel methodologies been developed for the direct sequencing of RBP-bound RNA, but a new class of miRNA (microRNA) target prediction algorithms trained on this data has emerged. In this article, we will explore and evaluate the next generation of animal miRNA target prediction algorithms, their relationship to more traditional prediction methods, and the implications of such methodologies for the future of miRNA target prediction and miRNA research as a whole.

Cell Density and Joint microRNA-133a and microRNA-696 Inhibition Enhance Differentiation and Contractile Function of Engineered Human Skeletal Muscle Tissues

To utilize three-dimensional (3D) engineered human skeletal muscle tissue for translational studies and in vitro studies of drug toxicity, there is a need to promote differentiation and functional behavior. In this study, we identified conditions to promote contraction of engineered human skeletal muscle bundles and examined the effects of transient inhibition of microRNAs (miRs) on myogenic differentiation and function of two-dimensional (2D) and 3D cultures of human myotubes. In 2D cultures, simultaneously inhibiting both miR-133a, which promotes myoblast proliferation, and miR-696, which represses oxidative metabolism, resulted in an increase in sarcomeric α-actinin protein and the metabolic coactivator PGC-1α protein compared to transfection with a scrambled miR sequence (negative control). Although PGC-1α was elevated following joint inhibition of miRs 133a and 696, there was no difference in myosin heavy chain (MHC) protein isoforms. 3D engineered human skeletal muscle myobundles seeded with 5 × 10(6) human skeletal myoblasts (HSkM)/mL and cultured for 2 weeks after onset of differentiation consistently did not contract when stimulated electrically, whereas those seeded with myoblasts at 10 × 10(6) HSkM/mL or higher did contract. When HSkM were transfected with both anti-miRs and seeded into fibrin hydrogels and cultured for 2 weeks under static conditions, twitch and tetanic specific forces after electrical stimulation were greater than for myobundles prepared with HSkM transfected with scrambled sequences. Immunofluorescence and Western blots of 3D myobundles indicate that anti-miR-133a or anti-miR-696 treatment led to modest increases in slow MHC, but no consistent increase in fast MHC. Similar to results in 2D, only myobundles prepared with myoblasts treated with anti-miR-133a and anti-miR-696 produced an increase in PGC-1α mRNA. PGC-1α targets were differentially affected by the treatment. HIF-2α mRNA showed an expression pattern similar to that of PGC-1α mRNA, but COXII mRNA levels were not affected by the anti-miRs. Overall, joint inhibition of miR-133a and miR-696 accelerated differentiation, elevated the metabolic coactivator PGC-1α, and increased the contractile force in 3D engineered human skeletal muscle bundles.

Prediction of miRNA-mRNA Interactions Using miRGate

miRGate ( http://mirgate.bioinfo.cnio.es /) is a freely available database that contains predicted and experimentally validated microRNA-messenger RNA (miRNA-mRNA) target pairs. This resource includes novel predictions from five well-established algorithms, but recalculated from a common and comprehensive sequence dataset. It includes all 3'-UTR sequences of all known genes of the three more widely employed genomes (human, mouse, and rat), and all annotated miRNA sequences from those genomes. Besides, it also contains predictions for all genes in human targeted by miRNA viruses such as Epstein-Barr and Kaposi sarcoma-associated herpes virus.The approach intends to circumvent one of the main drawbacks in this area, as diverse sequences and gene database versions cause poor overlap among different target prediction methods even with experimentally confirmed targets. As a result, miRGate predictions have been successfully validated using functional assays in several laboratories.This chapter describes how a user can access target information via miRGate's web interface. It also shows how automatically access the database through the programmatic interface based on representational state transfer services (REST), using the application programming interface (API) available at http://mirgate.bioinfo.cnio.es/API .

Integrated Strategy Improves the Prediction Accuracy of miRNA in Large Dataset

MiRNAs are short non-coding RNAs of about 22 nucleotides, which play critical roles in gene expression regulation. The biogenesis of miRNAs is largely determined by the sequence and structural features of their parental RNA molecules. Based on these features, multiple computational tools have been developed to predict if RNA transcripts contain miRNAs or not. Although being very successful, these predictors started to face multiple challenges in recent years. Many predictors were optimized using datasets of hundreds of miRNA samples. The sizes of these datasets are much smaller than the number of known miRNAs. Consequently, the prediction accuracy of these predictors in large dataset becomes unknown and needs to be re-tested. In addition, many predictors were optimized for either high sensitivity or high specificity. These optimization strategies may bring in serious limitations in applications. Moreover, to meet continuously raised expectations on these computational tools, improving the prediction accuracy becomes extremely important. In this study, a meta-predictor mirMeta was developed by integrating a set of non-linear transformations with meta-strategy. More specifically, the outputs of five individual predictors were first preprocessed using non-linear transformations, and then fed into an artificial neural network to make the meta-prediction. The prediction accuracy of meta-predictor was validated using both multi-fold cross-validation and independent dataset. The final accuracy of meta-predictor in newly-designed large dataset is improved by 7% to 93%. The meta-predictor is also proved to be less dependent on datasets, as well as has refined balance between sensitivity and specificity. This study has two folds of importance: First, it shows that the combination of non-linear transformations and artificial neural networks improves the prediction accuracy of individual predictors. Second, a new miRNA predictor with significantly improved prediction accuracy is developed for the community for identifying novel miRNAs and the complete set of miRNAs. Source code is available at:https://github.com/xueLab/mirMeta

A priori, de novo mathematical exploration of gene expression mechanism via regression viewpoint with briefly cataloged modeling antiquity

Various algorithms have been devised to mathematically model the dynamic mechanism of the gene expression data. Gillespie’s stochastic simulation (GSSA) has been exceptionally primal for chemical reaction synthesis with future ameliorations. Several other mathematical techniques such as differential equations, thermodynamic models and Boolean models have been implemented to optimally and effectively represent the gene functioning. We present a novel mathematical framework of gene expression, undertaking the mathematical modeling of the transcription and translation phases, which is a detour from conventional modeling approaches. These subprocesses are inherent to every gene expression, which is implicitly an experimental outcome. As we foresee, there can be modeled a generality about some basal translation or transcription values that correspond to a particular assay.

Effect of Dynamic Interaction between microRNA and Transcription Factor on Gene Expression

MicroRNAs (miRNAs) are endogenous noncoding RNAs which participate in diverse biological processes in animals and plants. They are known to join together with transcription factors and downstream gene, forming a complex and highly interconnected regulatory network. To recognize a few overrepresented motifs which are expected to perform important elementary regulatory functions, we constructed a computational model of miRNA-mediated feedforward loops (FFLs) in which a transcription factor (TF) regulates miRNA and targets gene. Based on the different dynamic interactions between miRNA and TF on gene expression, four possible structural topologies of FFLs with two gate functions (AND gate and OR gate) are introduced. We studied the dynamic behaviors of these different motifs. Furthermore, the relationship between the response time and maximal activation velocity of miRNA was investigated. We found that the curve of response time shows nonmonotonic behavior in Co1 loop with OR gate. This may help us to infer the mechanism of miRNA binding to the promoter region. At last we investigated the influence of important parameters on the dynamic response of system. We identified that the stationary levels of target gene in all loops were insensitive to the initial value of miRNA.

Circulating microRNAs in cancer: Hope or hype?

Circulating miRNAs are a novel class of stable, minimally invasive disease biomarkers that are considered to be valuable in diagnosis, prognosis and treatment response monitoring. Unlike intracellular miRNAs, circulating miRNAs are released from their producer cells and, based on their targeted functions, they may shuttle in and out of circulation. Their discovery has opened up new avenues for clinical realms and led to a quest for targeted biomarkers. Subsequently, as more cell-free miRNAs are being discovered, their expression is expected to provide precise information regarding disease progression and treatment outcomes, thereby fostering personalized therapeutic strategies. The significance of circulating miRNAs capitalizes on the fact that they are highly stable in body fluids and their expression levels can be detected by common techniques such as qPCR and microarray. However, discrepancies have started to emerge in terms of their reliability and their response under physiological and pathological conditions. Functional studies are still pending, which may determine whether circulating miRNAs play a role as a central component or just as an auxiliary tuner. Also, the distinct clinical signatures that they display have never been subjected to an extensive critical review and experimental validation. As a consequence, the applicability of circulating miRNAs remains a matter of deliberation, despite many intriguing perspectives about their competency. In this review, we highlight some ambiguous issues with the application of circulating miRNAs, which may warrant an immediate consideration. We propose that the circulating miRNA domain needs to be reevaluated to authenticate their specific role and to probe whether they actually carry any clinical weightage.

Understanding microRNA-mediated gene regulatory networks through mathematical modelling

The discovery of microRNAs (miRNAs) has added a new player to the regulation of gene expression. With the increasing number of molecular species involved in gene regulatory networks, it is hard to obtain an intuitive understanding of network dynamics. Mathematical modelling can help dissecting the role of miRNAs in gene regulatory networks, and we shall here review the most recent developments that utilise different mathematical modelling approaches to provide quantitative insights into the function of miRNAs in the regulation of gene expression. Key miRNA regulation features that have been elucidated via modelling include: (i) the role of miRNA-mediated feedback and feedforward loops in fine-tuning of gene expression; (ii) the miRNA–target interaction properties determining the effectiveness of miRNA-mediated gene repression; and (iii) the competition for shared miRNAs leading to the cross-regulation of genes. However, there is still lack of mechanistic understanding of many other properties of miRNA regulation like unconventional miRNA–target interactions, miRNA regulation at different sub-cellular locations and functional miRNA variant, which will need future modelling efforts to deal with. This review provides an overview of recent developments and challenges in this field.

MicroRNA profiling identifies MiR-195 suppresses osteosarcoma cell metastasis by targeting CCND1

Metastasis is a leading cause of mortality for osteosarcoma patients. The molecular pathological mechanism remains to be elucidated. In the previously study, we established two osteosarcoma cell lines with different metastatic potentials. Differential expressed genes and proteins regarding metastatic ability have been identified. MicroRNAs are important regulators in tumorigenesis and tumor progression. In this study, microRNA microarray was used to assess the differential expressed miRNAs level between these two cell lines. One of the top ranked miRNAs-miR-195 was identified highly expressing in lowly metastatic cells. It was showed that over-expression of miR-195 substantially inhibits migration and invasion of osteosarcoma cells in vitro and pulmonary metastasis formation in vivo. Meanwhile, CCND1 was identified as the target gene of miR-195 and further studied. More importantly, Using real-time PCR, we evaluated the expression of miR-195 and CCND1 in osteosarcoma samples from 107 frozen biopsy tissues and 99 formalin- or paraformalin-fixed, paraffin-embedded (FFPE) tissues. Results indicated lowly expressed miR-195 or highly CCND1 correlated with positive overall survival and their expression inverse relate to each other. In summary, our study suggests miR-195 function as a tumor metastasis suppressor gene by down-regulating CCND1 and can be used as a potential target in the treatment of osteosarcoma.

Probing the Limits to MicroRNA-Mediated Control of Gene Expression

According to the ‘ceRNA hypothesis’, microRNAs (miRNAs) may act as mediators of an effective positive interaction between long coding or non-coding RNA molecules, carrying significant potential implications for a variety of biological processes. Here, inspired by recent work providing a quantitative description of small regulatory elements as information-conveying channels, we characterize the effectiveness of miRNA-mediated regulation in terms of the optimal information flow achievable between modulator (transcription factors) and target nodes (long RNAs). Our findings show that, while a sufficiently large degree of target derepression is needed to activate miRNA-mediated transmission, (a) in case of differential mechanisms of complex processing and/or transcriptional capabilities, regulation by a post-transcriptional miRNA-channel can outperform that achieved through direct transcriptional control; moreover, (b) in the presence of large populations of weakly interacting miRNA molecules the extra noise coming from titration disappears, allowing the miRNA-channel to process information as effectively as the direct channel. These observations establish the limits of miRNA-mediated post-transcriptional cross-talk and suggest that, besides providing a degree of noise buffering, this type of control may be effectively employed in cells both as a failsafe mechanism and as a preferential fine tuner of gene expression, pointing to the specific situations in which each of these functionalities is maximized.

The discovery of RNA interference has revolutionized the decades’ old view of RNAs as mere intermediaries between DNA and proteins in the gene expression workflow. MicroRNAs (or miRNAs), in particular, have been shown to be able to both stabilize the protein output by buffering transcriptional noise and to create an effective positive interaction between the levels of their target RNAs through a simple competition mechanism known as ‘ceRNA effect’. With miRNAs commonly targeting multiple species of RNAs, the potential implication is that RNAs could regulate each other through extended miRNA-mediated interaction networks. Such cross-talk is certainly active in many specific cases (like cell differentiation), but it’s unclear whether the degree of regulation of gene expression achievable through post-transcriptional miRNA-mediated coupling can effectively overcome the one obtained through other mechanisms, e.g. by direct transcriptional control via DNA-binding factors. This work quantifies the maximal post-transcriptional regulatory power achievable by miRNA-mediated cross-talk, characterizing the circumstances in which indirect control outperforms direct one. The emerging scenario suggests that, in addition to its widely recognized noise-buffering role, miRNA-mediated control may indeed act as a master regulator of gene expression.

Muscle Expression of SOD1(G93A) Modulates microRNA and mRNA Transcription Pattern Associated with the Myelination Process in the Spinal Cord of Transgenic Mice

A crucial system severely affected in several neuromuscular diseases is the loss of effective connection between muscle and nerve, leading to a pathological non-communication between the two tissues. One of the best examples of impaired interplay between muscle and nerve is Amyotrophic Lateral Sclerosis, a neurodegenerative disease characterized by degeneration of motor neurons and muscle atrophy. Increasing evidences suggest that damage to motor neurons is enhanced by alterations in the neighboring non-neuronal cells and indicate that altered skeletal muscle might be the source of signals that impinge motor neuron activity and survival. Here we investigated whether muscle selective expression of SOD1^G93A mutant gene modulates mRNAs and miRNAs expression at the level of spinal cord of MLC/SOD1^G93A mice. Using a Taqman array, the Affymetrix Mouse Gene 2.0 ST approach and the MiRwalk 2.0 database, which provides information on miRNA and their predicted target genes, we revealed that muscle specific expression of SOD1^G93A modulates relevant molecules of the genetic and epigenetic circuitry of myelin homeostasis in spinal cord of transgenic mice. Our study provides insights into the pathophysiological interplay between muscle and nerve and supports the hypothesis that muscle is a source of signals that can either positively or negatively affect the nervous system.

Placental transcriptome in development and pathology: expression, function, and methods of analysis

The placenta is the essential organ of mammalian pregnancy and errors in its development and function are associated with a wide range of human pathologies of pregnancy. Genome sequencing has led to methods for investigation of the transcriptome (all expressed RNA species) using microarrays and next-generation sequencing, and implementation of these techniques has identified many novel species of RNA including: micro-RNA, long noncoding RNA, and circular RNA. These species can physically interact with both each other and regulatory proteins to modify gene expression and messenger RNA to protein translation. Transcriptome analysis is actively used to investigate placental development and dysfunction in pathologies ranging from preeclampsia and fetal growth restriction to preterm labor. Genome-wide gene expression analysis is also being applied to identify prognostic and diagnostic biomarkers of these disorders. In this comprehensive review we summarize transcriptome biology, methods of isolation and analysis, application to placental development and pathology, and use in diagnostic analysis in maternal blood. Key information for analysis methods is organized into quick reference tables where current analysis techniques and tools are cited and compared. We have created this review as a practical guide and starting reference for those interested in beginning an investigation into the transcriptome of the placenta.

The RNA world in the 21st century-a systems approach to finding non-coding keys to clinical questions

There was evidence that RNAs are a functionally rich class of molecules not only since the arrival of the next-generation sequencing technology. Non-coding RNAs (ncRNA) could be the key to accelerated diagnosis and enhanced prediction of disease and therapy outcomes as well as the design of advanced therapeutic strategies to overcome yet unsatisfactory approaches.In this review, we discuss the state of the art in RNA systems biology with focus on the application in the systems biomedicine field. We propose guidelines for analysing the role of microRNAs and long non-coding RNAs in human pathologies. We introduce RNA expression profiling and network approaches for the identification of stable and effective RNomics-based biomarkers, providing insights into the role of ncRNAs in disease regulation. Towards this, we discuss ways to model the dynamics of gene regulatory networks and signalling pathways that involve ncRNAs. We also describe data resources and computational methods for finding putative mechanisms of action of ncRNAs. Finally, we discuss avenues for the computer-aided design of novel RNA-based therapeutics.

Effect of 90Sr internal emitter on gene expression in mouse blood

Background

The radioactive isotope Strontium-90 (⁹⁰Sr) may be released as a component of fallout from nuclear accidents, or in the event of a radiological incident such as detonation of an improvised nuclear device, and if ingested poses a significant health risk to exposed individuals. In order to better understand the response to ⁹⁰Sr, using an easily attainable and standard biodosimetry sample fluid, we analyzed the global transcriptomic response of blood cells in an in vivo model system.

Results

We injected C57BL/6 mice with a solution of 90SrCl2 and followed them over a 30-day period. At days 4, 7, 9, 25 and 30, we collected blood and isolated RNA for microarray analyses. These days corresponded to target doses in a range from 1–5 Gy. We investigated changes in mRNA levels using microarrays, and changes in specific microRNA (miRNA) predicted to be involved in the response using qRT-PCR. We identified 8082 differentially expressed genes in the blood of mice exposed to ⁹⁰Sr compared with controls. Common biological functions were affected throughout the study, including apoptosis of B and T lymphocytes, and atrophy of lymphoid organs. Cellular functions such as RNA degradation and lipid metabolism were also affected during the study. The broad down regulation of genes observed in our study suggested a potential role for miRNA in gene regulation. We tested candidate miRNAs, mmu-miR-16, mmu-miR-124, mmu-miR-125 and mmu-mir-21; and found that all were induced at the earliest time point, day 4.

Conclusions

Our study is the first to report the transcriptomic response of blood cells to the internal emitter ⁹⁰Sr in mouse and a possible role for microRNA in gene regulation after ⁹⁰Sr exposure. The most dramatic effect was observed on gene expression related to B-cell development and RNA maintenance. These functions were affected by genes that were down regulated throughout the study, suggesting severely compromised antigen response, which may be a result of the deposition of the radioisotope proximal to the hematopoietic compartment in bone.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1774-z) contains supplementary material, which is available to authorized users.

Detection of miRNA regulatory effect on triple negative breast cancer transcriptome

Identifying key microRNAs (miRNAs) contributing to the genesis and development of a particular disease is a focus of many recent studies. We introduce here a rank-based algorithm to detect miRNA regulatory activity in cancer-derived tissue samples which combines measurements of gene and miRNA expression levels and sequence-based target predictions. The method is designed to detect modest but coordinated changes in the expression of sequence-based predicted target genes. We applied our algorithm to a cohort of 129 tumour and healthy breast tissues and showed its effectiveness in identifying functional miRNAs possibly involved in the disease. These observations have been validated using an independent publicly available breast cancer dataset from The Cancer Genome Atlas. We focused on the triple negative breast cancer subtype to highlight potentially relevant miRNAs in this tumour subtype. For those miRNAs identified as potential regulators, we characterize the function of affected target genes by enrichment analysis. In the two independent datasets, the affected targets are not necessarily the same, but display similar enriched categories, including breast cancer related processes like cell substrate adherens junction, regulation of cell migration, nuclear pore complex and integrin pathway. The R script implementing our method together with the datasets used in the study can be downloaded here (http://bioinfo-out.curie.fr/projects/targetrunningsum).

The microRNA Expression Profile in Donation after Cardiac Death (DCD) Livers and Its Ability to Identify Primary Non Function

Donation after cardiac death (DCD) livers are marginal organs for transplant and their use is associated with a higher risk of primary non function (PNF) or early graft dysfunction (EGD). The aim was to determine if microRNA (miRNA) was able to discriminate between DCD livers of varying clinical outcome. DCD groups were categorized as PNF retransplanted within a week (n=7), good functional outcome (n=7) peak aspartate transaminase (AST) ≤ 1000 IU/L and EGD (n=9) peak AST ≥ 2500 IU/L. miRNA was extracted from archival formalin fixed post-perfusion tru-cut liver biopsies. High throughput expression analysis was performed using miRNA arrays. Bioinformatics for expression data analysis was performed and validated with real time quantitative PCR (RT-qPCR). The function of miRNA of interest was investigated using computational biology prediction algorithms. From the array analysis 16 miRNAs were identified as significantly different (p<0.05). On RT-qPCR miR-155 and miR-940 had the highest expression across all three DCD clinical groups. Only one miRNA, miR-22, was validated with marginal significance, to have differential expression between the three groups (p=0.049). From computational biology miR-22 was predicted to affect signalling pathways that impact protein turnover, metabolism and apoptosis/cell cycle. In conclusion, microRNA expression patterns have a low diagnostic potential clinically in discriminating DCD liver quality and outcome.

Identification of microRNA genes in three opisthorchiids

Background

Opisthorchis felineus, O. viverrini, and Clonorchis sinensis (family Opisthorchiidae) are parasitic flatworms that pose a serious threat to humans in some countries and cause opisthorchiasis/clonorchiasis. Chronic disease may lead to a risk of carcinogenesis in the biliary ducts. MicroRNAs (miRNAs) are small noncoding RNAs that control gene expression at post-transcriptional level and are implicated in the regulation of various cellular processes during the parasite- host interplay. However, to date, the miRNAs of opisthorchiid flukes, in particular those essential for maintaining their complex biology and parasitic mode of existence, have not been satisfactorily described.

Methodology/Principal Findings

Using a SOLiD deep sequencing-bioinformatic approach, we identified 43 novel and 18 conserved miRNAs for O. felineus (miracidia, metacercariae and adult worms), 20 novel and 16 conserved miRNAs for O. viverrini (adult worms), and 33 novel and 18 conserved miRNAs for C. sinensis (adult worms). The analysis of the data revealed differences in the expression level of conserved miRNAs among the three species and among three the developmental stages of O. felineus. Analysis of miRNA genes revealed two gene clusters, one cluster-like region and one intronic miRNA in the genome. The presence and structure of the two gene clusters were validated using a PCR-based approach in the three flukes.

Conclusions

This study represents a comprehensive description of miRNAs in three members of the family Opistorchiidae, significantly expands our knowledge of miRNAs in multicellular parasites and provides a basis for understanding the structural and functional evolution of miRNAs in these metazoan parasites. Results of this study also provides novel resources for deeper understanding the complex parasite biology, for further research on the pathogenesis and molecular events of disease induced by the liver flukes. The present data may also facilitate the development of novel approaches for the prevention and treatment of opisthorchiasis/clonorchiasis.

Liver flukes of the family Opisthorchiidae cause diseases of the hepatobiliary system, known as opisthorchiasis/clonorchiasis. The chronic forms of these diseases greatly increase the risk of cancer developing in the biliary ducts. Much has been elucidated regarding the developmental biology of opisthorchiid flukes and the molecular pathological effects on the definitive host; however, the role of microRNAs (short non-coding RNAs) capable of influencing the pathogenic process and host-parasite interactions have not yet been comprehensively studied. The aim of the present work was to identify the miRNA genes of the liver flukes and provide a basis for further investigating the roles of these miRNAs in the complex opisthorchiidae life cycle and the pathogenesis of disease.

miRGate: a curated database of human, mouse and rat miRNA-mRNA targets

MicroRNAs (miRNAs) are small non-coding elements involved in the post-transcriptional down-regulation of gene expression through base pairing with messenger RNAs (mRNAs). Through this mechanism, several miRNA-mRNA pairs have been described as critical in the regulation of multiple cellular processes, including early embryonic development and pathological conditions. Many of these pairs (such as miR-15 b/BCL2 in apoptosis or BART-6/BCL6 in diffuse large B-cell lymphomas) were experimentally discovered and/or computationally predicted. Available tools for target prediction are usually based on sequence matching, thermodynamics and conservation, among other approaches. Nevertheless, the main issue on miRNA-mRNA pair prediction is the little overlapping results among different prediction methods, or even with experimentally validated pairs lists, despite the fact that all rely on similar principles. To circumvent this problem, we have developed miRGate, a database containing novel computational predicted miRNA-mRNA pairs that are calculated using well-established algorithms. In addition, it includes an updated and complete dataset of sequences for both miRNA and mRNAs 3'-Untranslated region from human (including human viruses), mouse and rat, as well as experimentally validated data from four well-known databases. The underlying methodology of miRGate has been successfully applied to independent datasets providing predictions that were convincingly validated by functional assays. miRGate is an open resource available at http://mirgate.bioinfo.cnio.es. For programmatic access, we have provided a representational state transfer web service application programming interface that allows accessing the database at http://mirgate.bioinfo.cnio.es/API/ Database URL: http://mirgate.bioinfo.cnio.es

Mathematical modeling of combinatorial regulation suggests that apparent positive regulation of targets by miRNA could be an artifact resulting from competition for mRNA

MicroRNAs bind to and regulate the abundance and activity of target messenger RNA through sequestration, enhanced degradation, and suppression of translation. Although miRNA have a predominantly negative effect on the target protein concentration, several reports have demonstrated a positive effect of miRNA, i.e., increase in target protein concentration on miRNA overexpression and decrease in target concentration on miRNA repression. miRNA-target pair-specific effects such as protection of mRNA degradation owing to miRNA binding can explain some of these effects. However, considering such pairs in isolation might be an oversimplification of the RNA biology, as it is known that one miRNA interacts with several targets, and conversely target mRNA are subject to regulation by several miRNAs. We formulate a mathematical model of this combinatorial regulation of targets by multiple miRNA. Through mathematical analysis and numerical simulations of this model, we show that miRNA that individually have a negative effect on their targets may exhibit an apparently positive net effect when the concentration of one miRNA is experimentally perturbed by repression/overexpression in such a multi-miRNA multitarget situation. We show that this apparent unexpected effect is due to competition and will not be observed when miRNA interact noncompetitively with the target mRNA. This result suggests that some of the observed unusual positive effects of miRNA may be due to the combinatorial complexity of the system rather than due to any inherently unusual positive effect of the miRNA on its target.

Plasticity-related microRNA and their potential contribution to the maintenance of long-term potentiation

Long-term potentiation (LTP) is a form of synaptic plasticity that is an excellent model for the molecular mechanisms that underlie memory. LTP, like memory, is persistent, and both are widely believed to be maintained by a coordinated genomic response. Recently, a novel class of non-coding RNA, microRNA, has been implicated in the regulation of LTP. MicroRNA negatively regulate protein synthesis by binding to specific messenger RNA response elements. The aim of this review is to summarize experimental evidence for the proposal that microRNA play a major role in the regulation of LTP. We discuss a growing body of research which indicates that specific microRNA regulate synaptic proteins relevant to LTP maintenance, as well as studies that have reported differential expression of microRNA in response to LTP induction. We conclude that microRNA are ideally suited to contribute to the regulation of LTP-related gene expression; microRNA are pleiotropic, synaptically located, tightly regulated, and function in response to synaptic activity. The potential impact of microRNA on LTP maintenance as regulators of gene expression is enormous.

Toxin effect on protein biosynthesis in eukaryotic cells: a simple kinetic model

A model for toxin inhibition of protein synthesis inside eukaryotic cells is presented. Mitigation of this effect by introduction of an antibody is also studied. Antibody and toxin (ricin) initially are delivered outside the cell. The model describes toxin internalization from the extracellular into the intracellular domain, its transport to the endoplasmic reticulum (ER) and the cleavage inside the ER into the RTA and RTB chains, the release of RTA into the cytosol, inactivation (depurination) of ribosomes, and the effect on translation. The model consists of a set of ODEs which are solved numerically. Numerical results are illustrated by figures and discussed.

Dynamics of miRNA driven feed-forward loop depends upon miRNA action mechanisms

Background

We perform the theoretical analysis of a gene network sub-system, composed of a feed-forward loop, in which the upstream transcription factor regulates the target gene via two parallel pathways: directly, and via interaction with miRNA.

Results

As the molecular mechanisms of miRNA action are not clear so far, we elaborate three mathematical models, in which miRNA either represses translation of its target or promotes target mRNA degradation, or is not re-used, but degrades along with target mRNA. We examine the feed-forward loop dynamics quantitatively at the whole time interval of cell cycle. We rigorously proof the uniqueness of solutions to the models and obtain the exact solutions in one of them analytically.

Conclusions

We have shown that different mechanisms of miRNA action lead to a variety of types of dynamical behavior of feed-forward loops. In particular, we found that the ability of feed-forward loop to dampen fluctuations introduced by transcription factor is the model and parameter dependent feature. We also discuss how our results could help a biologist to infer the mechanism of miRNA action.

What do all the (human) micro-RNAs do?

Background

Micro-RNAs (miRNA) are attributed to the systems biological role of a regulatory mechanism of the expression of protein coding genes. Research has identified miRNAs dysregulations in several but distinct pathophysiological processes, which hints at distinct systems-biology functions of miRNAs. The present analysis approached the role of miRNAs from a genomics perspective and assessed the biological roles of 2954 genes and 788 human miRNAs, which can be considered to interact, based on empirical evidence and computational predictions of miRNA versus gene interactions.

Results

From a genomics perspective, the biological processes in which the genes that are influenced by miRNAs are involved comprise of six major topics comprising biological regulation, cellular metabolism, information processing, development, gene expression and tissue homeostasis. The usage of this knowledge as a guidance for further research is sketched for two genetically defined functional areas: cell death and gene expression. Results suggest that the latter points to a fundamental role of miRNAs consisting of hyper-regulation of gene expression, i.e., the control of the expression of such genes which control specifically the expression of genes.

Conclusions

Laboratory research identified contributions of miRNA regulation to several distinct biological processes. The present analysis transferred this knowledge to a systems-biology level. A comprehensible and precise description of the biological processes in which the genes that are influenced by miRNAs are notably involved could be made. This knowledge can be employed to guide future research concerning the biological role of miRNA (dys-) regulations. The analysis also suggests that miRNAs especially control the expression of genes that control the expression of genes.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-976) contains supplementary material, which is available to authorized users.

Melatonin, noncoding RNAs, messenger RNA stability and epigenetics--evidence, hints, gaps and perspectives

Melatonin is a highly pleiotropic regulator molecule, which influences numerous functions in almost every organ and, thus, up- or down-regulates many genes, frequently in a circadian manner. Our understanding of the mechanisms controlling gene expression is actually now expanding to a previously unforeseen extent. In addition to classic actions of transcription factors, gene expression is induced, suppressed or modulated by a number of RNAs and proteins, such as miRNAs, lncRNAs, piRNAs, antisense transcripts, deadenylases, DNA methyltransferases, histone methylation complexes, histone demethylases, histone acetyltransferases and histone deacetylases. Direct or indirect evidence for involvement of melatonin in this network of players has originated in different fields, including studies on central and peripheral circadian oscillators, shift work, cancer, inflammation, oxidative stress, aging, energy expenditure/obesity, diabetes type 2, neuropsychiatric disorders, and neurogenesis. Some of the novel modulators have also been shown to participate in the control of melatonin biosynthesis and melatonin receptor expression. Future work will need to augment the body of evidence on direct epigenetic actions of melatonin and to systematically investigate its role within the network of oscillating epigenetic factors. Moreover, it will be necessary to discriminate between effects observed under conditions of well-operating and deregulated circadian clocks, and to explore the possibilities of correcting epigenetic malprogramming by melatonin.

Biomarkers for virus-induced hepatocellular carcinoma (HCC)

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, and is advanced by severe viral hepatitis B or C (HBV or HCV) as well as alcoholic liver disease. Many patients with early disease are asymptomatic therefore HCC is frequently diagnosed late requiring costly surgical resection or transplantation. The available non-invasive detections systems are based on the clinical utility of alpha fetoprotein (AFP) measurement, together with ultrasound and other more sensitive imaging techniques. The hallmark of liver disease and its propensity to develop into fully blown HCC is depended on several factors including the host genetic make-up and immune responses. While common symptoms involve diarrhea, bone pain, dyspnea, intraperitoneal bleeding, obstructive jaundice, and paraneoplastic syndrome, the evolution of cell and immune markers is important to understand viral induced liver cancers in humans. The circulating miRNA, cell and immune based HCC biomarkers are imperative candidates to successfully develop strategies to restrain liver injury. The current molecular genetics and proteomic analysis have lead to the identification of number of key biomarkers for HCC for earlier diagnosis and more effective treatment of HCC patients. In this review article, we provide latest updates on the biomarkers of HBV or HCV-associated HCC and their co-evolutionary relationship with liver cancer.

Functional interactions among microRNAs and long noncoding RNAs

In mammals, the vast majority of transcripts expressed are noncoding RNAs, ranging from short RNAs (including microRNAs) to long RNAs spanning up to hundreds of kb. While the actions of microRNAs as destabilizers and repressors of the translation of protein-coding transcripts (mRNAs) have been studied in detail, the influence of microRNAs on long noncoding RNA (lncRNA) function is only now coming into view. Conversely, the influence of lncRNAs upon microRNA function is also rapidly emerging. In some cases, lncRNA stability is reduced through the interaction of specific miRNAs. In other cases, lncRNAs can act as microRNA decoys, with the sequestration of microRNAs favoring expression of repressed target mRNAs. Other lncRNAs derepress gene expression by competing with miRNAs for interaction with shared target mRNAs. Finally, some lncRNAs can produce miRNAs, leading to repression of target mRNAs. These microRNA-lncRNA regulatory paradigms modulate gene expression patterns that drive major cellular processes (such as cell differentiation, proliferation, and cell death) which are central to mammalian physiologic and pathologic processes. We review and summarize the types of microRNA-lncRNA crosstalk identified to-date and discuss their influence on gene expression programs.

Post-transcriptional regulation in the nucleus and cytoplasm: study of mean time to threshold (MTT) and narrow escape problem

Messenger RNAs (mRNAs) can be repressed and degraded by small non-coding RNA molecules. In this paper, we formulate a coarsegrained Markov-chain description of the post-transcriptional regulation of mRNAs by either small interfering RNAs (siRNAs) or microRNAs (miRNAs). We calculate the probability of an mRNA escaping from its domain before it is repressed by siRNAs/miRNAs via calculation of the mean time to threshold: when the number of bound siRNAs/miRNAs exceeds a certain threshold value, the mRNA is irreversibly repressed. In some cases, the analysis can be reduced to counting certain paths in a reduced Markov model. We obtain explicit expressions when the small RNA bind irreversibly to the mRNA and we also discuss the reversible binding case. We apply our models to the study of RNA interference in the nucleus, examining the probability of mRNAs escaping via small nuclear pores before being degraded by siRNAs. Using the same modelling framework, we further investigate the effect of small, decoy RNAs (decoys) on the process of post-transcriptional regulation, by studying regulation of the tumor suppressor gene, PTEN: decoys are able to block binding sites on PTEN mRNAs, thereby reducing the number of sites available to siRNAs/miRNAs and helping to protect it from repression. We calculate the probability of a cytoplasmic PTEN mRNA translocating to the endoplasmic reticulum before being repressed by miRNAs. We support our results with stochastic simulations.

MicroRNA miR-378 promotes BMP2-induced osteogenic differentiation of mesenchymal progenitor cells

Background

MicroRNAs (miRNAs) are a family of small, non-coding single-stranded RNA molecules involved in post-transcriptional regulation of gene expression. As such, they are believed to play a role in regulating the step-wise changes in gene expression patterns that occur during cell fate specification of multipotent stem cells. Here, we have studied whether terminal differentiation of C2C12 myoblasts is indeed controlled by lineage-specific changes in miRNA expression.

Results

Using a previously generated RNA polymerase II (Pol-II) ChIP-on-chip dataset, we show differential Pol-II occupancy at the promoter regions of six miRNAs during C2C12 myogenic versus BMP2-induced osteogenic differentiation. Overexpression of one of these miRNAs, miR-378, enhances Alp activity, calcium deposition and mRNA expression of osteogenic marker genes in the presence of BMP2.

Conclusions

Our results demonstrate a previously unknown role for miR-378 in promoting BMP2-induced osteogenic differentiation.

RILES, a novel method for temporal analysis of the in vivo regulation of miRNA expression

Novel methods are required to investigate the complexity of microRNA (miRNA) biology and particularly their dynamic regulation under physiopathological conditions. Herein, a novel plasmid-based RNAi-Inducible Luciferase Expression System (RILES) was engineered to monitor the activity of endogenous RNAi machinery. When RILES is transfected in a target cell, the miRNA of interest suppresses the expression of a transcriptional repressor and consequently switch-ON the expression of the luciferase reporter gene. Hence, miRNA expression in cells is signed by the emission of bioluminescence signals that can be monitored using standard bioluminescence equipment. We validated this approach by monitoring in mice the expression of myomiRs-133, −206 and −1 in skeletal muscles and miRNA-122 in liver. Bioluminescence experiments demonstrated robust qualitative and quantitative data that correlate with the miRNA expression pattern detected by quantitative RT-PCR (qPCR). We further demonstrated that the regulation of miRNA-206 expression during the development of muscular atrophy is individual-dependent, time-regulated and more complex than the information generated by qPCR. As RILES is simple and versatile, we believe that this methodology will contribute to a better understanding of miRNA biology and could serve as a rationale for the development of a novel generation of regulatable gene expression systems with potential therapeutic applications.

Protective effect of caffeine against high sugar-induced transcription of microRNAs and consequent gene silencing: a study using lenses of galactosemic mice

PURPOSE

Previous studies have shown that caffeine prevents the formation of cataracts induced by a high-galactose diet and consequent oxidative stress. The objective of this study was to investigate if this protective effect is reflected in the attenuation of the transcription of microRNAs (miRNAs) known to induce apoptosis and cell death by gene silencing.

METHODS

Young CD-1 mice were fed either a normal laboratory diet or a diet containing 25% galactose with or without 1% caffeine. One week later, the animals were euthanized, and the lenses isolated and promptly processed for RNA isolation and subsequent preparation of cDNAs by reverse transcriptase reaction. Mature miRNA (miR)-specific cDNAs were then quantified with PCR in a 96-well microRNA-specific cassette using an ABI7900HT PCR machine.

RESULTS

As expected from previous studies, the lenses were positive for all 84 miRs corresponding to the miRNA probes present in the cassette wells. However, the levels of at least 19 miRs were significantly elevated in galactosemic lenses compared to those in the normal lenses. The majority are proapoptotic. Such elevation was inhibited by caffeine. This has been demonstrated for the first time.

CONCLUSIONS

Since aberrant elevation of miRNAs silences various genes and consequently deactivates protein translation, and since caffeine downregulates such aberration, the beneficial effect of caffeine could be attributed to its ability to suppress elevation of toxic miRs and consequent gene silencing.

Model composition through model reduction: a combined model of CD95 and NF-κB signaling pathways

Background

Many mathematical models characterizing mechanisms of cell fate decisions have been constructed recently. Their further study may be impossible without development of methods of model composition, which is complicated by the fact that several models describing the same processes could use different reaction chains or incomparable sets of parameters. Detailed models not supported by sufficient volume of experimental data suffer from non-unique choice of parameter values, non-reproducible results, and difficulty of analysis. Thus, it is necessary to reduce existing models to identify key elements determining their dynamics, and it is also required to design the methods allowing us to combine them.

Results

Here we propose a new approach to model composition, based on reducing several models to the same level of complexity and subsequent combining them together. Firstly, we suggest a set of model reduction tools that can be systematically applied to a given model. Secondly, we suggest a notion of a minimal complexity model. This model is the simplest one that can be obtained from the original model using these tools and still able to approximate experimental data. Thirdly, we propose a strategy for composing the reduced models together. Connection with the detailed model is preserved, which can be advantageous in some applications. A toolbox for model reduction and composition has been implemented as part of the BioUML software and tested on the example of integrating two previously published models of the CD95 (APO-1/Fas) signaling pathways. We show that the reduced models lead to the same dynamical behavior of observable species and the same predictions as in the precursor models. The composite model is able to recapitulate several experimental datasets which were used by the authors of the original models to calibrate them separately, but also has new dynamical properties.

Conclusion

Model complexity should be comparable to the complexity of the data used to train the model. Systematic application of model reduction methods allows implementing this modeling principle and finding models of minimal complexity compatible with the data. Combining such models is much easier than of precursor models and leads to new model properties and predictions.

Interplay of microRNAs, transcription factors and target genes: linking dynamic expression changes to function

MicroRNAs (miRNAs) are ubiquitously expressed small non-coding RNAs that, in most cases, negatively regulate gene expression at the post-transcriptional level. miRNAs are involved in fine-tuning fundamental cellular processes such as proliferation, cell death and cell cycle control and are believed to confer robustness to biological responses. Here, we investigated simultaneously the transcriptional changes of miRNA and mRNA expression levels over time after activation of the Janus kinase/Signal transducer and activator of transcription (Jak/STAT) pathway by interferon-γ stimulation of melanoma cells. To examine global miRNA and mRNA expression patterns, time-series microarray data were analysed. We observed delayed responses of miRNAs (after 24-48 h) with respect to mRNAs (12-24 h) and identified biological functions involved at each step of the cellular response. Inference of the upstream regulators allowed for identification of transcriptional regulators involved in cellular reactions to interferon-γ stimulation. Linking expression profiles of transcriptional regulators and miRNAs with their annotated functions, we demonstrate the dynamic interplay of miRNAs and upstream regulators with biological functions. Finally, our data revealed network motifs in the form of feed-forward loops involving transcriptional regulators, mRNAs and miRNAs. Additional information obtained from integrating time-series mRNA and miRNA data may represent an important step towards understanding the regulatory principles of gene expression.